What's really exciting for crypto is you have the entire US stock market, which is the largest stock market in the world. And then you have crypto, which is large but not as large. And all of a sudden, those pools of capital should fuse, which is great. I think software startups will have a much faster path to IPO as a result of crypto than they've had in the last 10 years.
How does this change end up accelerating the timeline to IPOs for some of these software companies, do you think?
We have made it so expensive to go public that if you were a microcap software company, if you were worth somewhere between one and a half to two billion, it's not economic to go public. Most of those companies get taken up by PE right away. And so, wouldn't it be amazing if you had a venue where small cap, high growth software companies were publicly traded?
Hey, I'm Mario, and this is The Generalist Podcast. As the saying goes, the future's already here. It's just not evenly distributed. On this show, I sit down with the founders, investors, and thinkers who are living in the future to help you see it earlier, understand it better, and capitalize on it. Today, I'm speaking with Tomasz Tunguz, the founder and managing partner of Theory Ventures. In just two years, Theory has raised nearly $700 million in capital and backed promising startups across AI, crypto, data analytics, and data infrastructure. As Tomasz shared, his goal with Theory isn't just to build another venture firm, but something closer to an investing corporation. In our conversation, we discuss what it takes to build a modern venture firm, and how Theory is accelerating deal flow analysis and market mapping with AI, Ethereum's existential moment, how the blockchain risks losing its dominance the same way that AWS lost ground to Microsoft Azure as the result of AI, and the 100 agent future of work, why knowledge workers might soon manage an army of AI agents each. I walked away from this conversation with new ideas on how AI might reshape work, how crypto is changing IPOs, and why we're living through what Tomasz calls the decade of data. This is a new podcast. So, if you like it, I hope you'll consider subscribing and joining us for some of the incredible episodes we have coming up. Now, here's my conversation with Tomasz.
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All right. Tomasz, it's so good to have you here. I've been an admirer of your writing and your public thinking basically since I first learned about what venture capital was, which is now almost a decade ago. And so, yeah, it's great to have you here. I'm super excited. And maybe we can begin with a little bit of an introduction to your career in venture. How did you end up here and running Theory Ventures?
Yeah, when I was 17 I started a company with my dad. It got me into startups. I was fascinated that you could start a company. And then after college, I studied mechanical engineering and computer science. And then I went to work for a startup that was founded by three alums from my school that ultimately ended up going public, and I was an early employee there and fell in love with it more, understood a bit more about it. Went to work at Google, built some large-scale machine learning systems with a phenomenal team for ad targeting, and then I've been a venture capitalist ever since. And I remember I was walking along the Embarcadero, which is the part of San Francisco that butts the water, and I saw an angel investor talking to a founder outside at a restaurant. I was like, 'Oh my gosh, I can't believe that's a career. I hope I get to do that one day.' And I was very lucky that I had the opportunity to start and now have a firm of our own called Theory.
And Theory, I think, is two, two and a half years old. Is that about right?
Okay. And you know, one of the things that I really admire and find really interesting about your approach to investing is you both invest in data companies, but also take a very data and thesis-driven approach to venture, which especially at the earlier stages isn't particularly common, especially not in the way that you guys do it. How did you sort of land on that approach as being the right one for you and the place where you felt you had a real edge?
Yeah, I think there are many different strategies that make money in venture. And the one that appeals to me the most is to perform really deep research. And that's the kind of work I really enjoy. It's gratifying because it helps us build as a firm, it helps us build networks of people who might be helpful to portfolio companies later. It helps us understand what's happening within those ecosystems so we can be helpful board members. And over time we think that knowledge is a compounding advantage. Right, the nuances of one wave, if you have them in a particular place stored, let's say in the organizational memory, is a huge advantage later on. Insight Partners is famous for this. They have a database of all the pitch decks and metrics over their entire existence. And that was a big inspiration. And you know, I look at some of the hedge funds that have done really well, they build information asymmetries that compound over time. I think the same thing is true in venture. The data sets are obviously quite different, but if we build the internal systems of knowledge the right way, then I think over long periods of time it compounds.
That's really interesting. I would say that, you know, one of the maybe more common ways of thinking about venture would be that these asymmetries get sanded away super fast because things just get, you know, competed away really, really quickly. What are the types of asymmetries that you see as actually being compounding or having the ability to compound for you guys?
The real asymmetry is just getting there earlier. Right? I mean, the venture capital asset class has grown from 8 to 250 billion in 15 years, let's say. And the amount of competition has increased dramatically. The number of different financial products that are offered to founders has grown. And that's wonderful for the ecosystem. Right? I think the bigger startup land, to broadly speaking, is, the better. The goal for us is to be able to carve out a niche. It doesn't have to be very large, but it has to be one where we think we can create a great business and drive strong multiples. And so to be able to do that, what we do is someone comes in on Monday, and I'll give you a story from our first intern, his name is Alex, who went on to start a company. And Alex, a brilliant guy, walks in on Monday during the investment committee and comes in with a 10-page paper. And he says, 'I don't believe GPUs are the future of AI. It'll all be ASICs, application-specific integrated circuits, which are chips that are designed to perform one operation like Bitcoin mining.' But in this case, transformer architectures. Now, there are startups that are doing that. And so, he walks in that Monday and we debate.
And I think that kind of investing is really fun. It's really fun because for half an hour every Monday, we sit there and within our team, we have a head of AI who is head of AI at three unicorns. And there's Lauren who built the healthcare practice at Palantir and sold contracts worth tens of millions of dollars to the largest healthcare companies in the world. And then we have two sales leaders from unicorns. And so, there's this composite team with many different backgrounds and experiences. And they each have a different perspective on the opportunity. And that composite view and that initial debate really leads us to decide, should we go and invest time here? Is this an investable opportunity? Is this within our scope? Does it meet our requirements? And that kind of investing is fun because out of that Monday, there's a lot of energy, right? If we find a theme or an idea that we're really interested in, there's a lot of energy. The whole firm pulls its resources, its network. And we can go and start a diligence process and a market map and really understand that space and we follow up on those market maps every Monday and then every month we review. And we present to each other what we've learned. And so, there is both a product for the organization, which is all of that research that we keep, and then there's an education of the entire firm. And so, with time, we should all become increasingly sophisticated investors or increasingly sophisticated on many different spaces.
So many interesting threads that I want to dive into there. One of which, almost a bit of a meta point, but it's interesting to me that your investment team sounds like so many of them are former operators, have really been in the weeds in industry. How did you think about building out the team that way and having sort of these more functional experts versus, you know, folks that maybe have longer investment track records? Like why is that the right approach for this style of firm?
So, I think the future of venture capital looks an awful lot like investing corporations. They don't look like partnerships. Why are venture capital firms partnerships? Well, it's because of our history. Silicon Valley started with six or seven men who would get together every Tuesday at a particular restaurant and each write a $50,000 check into a company and that was the first syndicate, right? And so, out of that two or three of them got together and said let's start a firm. We can raise some institutional capital. Capital markets were not very supportive, so the funds were small and then there were 10 or 15 of these firms up until the late '90s. And then all of a sudden there was kind of this institutionalization of the asset class post GFC, post the global financial crisis, and the asset class started to explode, right? But we have kept this notion of a partnership and there are many different reasons for that, but I think ultimately we are off- If you look at hedge funds, they're structured as investing corporations. If you look at private equity firms, they have investing teams and operations teams. And if you look at most major financial companies, they have different kind- there's a marketing team and there's a product team or technology team. And so, we think that's the future.
And in addition to that, it leads to better investment decisions because you have these different perspectives, right? We want our sales leaders' perspective on how effective a founder is at selling. We want our head of AI and our technical team's perspective on the technical depth of a company. And we need those conversations and that understanding to happen very quickly. We can't have a lot of additional meetings. Ideally we help the companies and give them guidance if we can and we have a perspective on their market or their sales strategy, and it helps inform our investment decision. And so, I think it just gives us a mosaic or a better triangulation of understanding a particular business or market.
Super interesting. I'm also interested to dig in a little bit deeper onto this thesis development piece. It sounds like, you know, on the one hand, you are constantly generating these theses as an organization and sort of having these Monday meetings and chasing down new leads, but also you've sort of organized the firm a bit around a few mega theses that you're deciding to really go deep on, sort of data, AI, crypto. There you have, you know, much sharper lenses around those different things, but how did you sort of land on those as, you know, let's say the sort of super narratives that you're following, and how do you sort of convince yourself that these are the places where we really have to go deep so you don't get stuck, you know, chasing a dead end or chasing something that's so broad that you, you know, would really actually end up having no edge?
All of them are underpinned by data. Modern data stack, databases, visualization, that's data. AI, machine learning, all of that's data. And blockchains, well, that's just a different kind of database. Right? So, they're just data systems broadly written, and they are sold to different buyers.
That's really interesting. So then, what is the deep interest in data systems there? Like, why is that the thing that you're like, this is the big opportunity for us?
Yes. Part of it is personal, right?
So, number one is I love data. I think the second thing is they create really big companies. I mean, Databricks and Snowflake in the modern data stack are both decacorns, maybe we'll see them becoming centacorns. Within the world of AI, all right, you have Anthropic and OpenAI and many others that will become decacorns. And then within the world of blockchains, I mean, you have Ethereum is worth 350 billion, Solana is worth 90 billion. So, you have incredibly large outcomes. That's one. Two, there's a combination, so all of these markets have technical innovation, faster databases, in-memory databases, better forms of decentralization, new AI architectures. Will it be transformers? Will it be diffusion models? Are they state-space models? And so, there's a technical component that is fun to understand, and then there's a go-to-market component, right? And so, that's fascinating, and it filters, right? There's less competition in very technical domains, just because it requires a particular set of expertise and a desire to understand it. And so, the combination of those two things, really, really large markets, the sort of barrier to entry for complex topics, and then the last thing I'd say is all of these categories are like of the moment, right? Like they're very interesting categories, they're capital efficient, and so that makes it fun, plus the replacement cycles are fast. So, in venture capital, we might invest in a company and work with that company for 5, 10, maybe 15 years, but ideally, there's the cycles of- it's not like nuclear reactors, right? Let's say awesome space, but a nuclear reactor takes 10 years to build, and then the next generation is probably 50 to 60 years from now. So, you might be able to invest in one nuclear reactor company in your lifetime, but you can invest in many data companies in any point in an investment career.
I think to a certain extent everyone's interests are sort of inscrutable even to themselves. Like it's hard for, you know, if someone asked me, 'Why do I like writing?' It would not be an easy question to answer, but to the extent that you can articulate it, like, why do you love data? Like, what is it that speaks to you about that as something to spend your time on? What is the elegance of these business models that really animate something in you?
Well, it's all understanding. I remember being in- so I had this amazing professor in grad school. His name was Ming Fang, and I studied control systems. And our two final exams, one was building the autopilot system for a Boeing 747 given only six sensors. And then the other one, which was a real use case, was imagine you have to receive a signal from a satellite, and there's a pad that has six actuators, and those six actuators move the receiver. And you have to move that receiver in real time to maximize the signal given earthquakes and the earth moving. And so, you know, whatever, like cool technical problems, we learned very basic control systems. And I was just fascinated by the fact that we could take these sensor data and actually make something that was magical. Right? Like a plane can fly by itself. I drive in a car that- well, I don't really drive the car anymore. The car drives itself. And all of that is as a result of a whole bunch of sensor data that's coming off some telemetry. And the same thing, you know, he was doing something in the stock market. And so, it's kind of like fracking. It's kind of like oil. Where you take this thing that comes out of the ground, and then you can do everything. I mean, you can make gasoline to put in a car from oil. You can make plastics to have a Tupperware container to save your applesauce. Or you can make clothes from oil. Right? And so, I think it's this unbelievably useful raw ingredient, and we're getting better and better at it. Like the whole world of data before, say 2010, was focused on the very finest grade of oil, Brent, let's say, which was structured data. Stuff that looks like it's in Excel or could fit in a structured database. And then over the last, say, 15 years, we've been learning how to frack data. We've been taking this raw unstructured data, the Word documents, the conversations that you and I have, the podcast, blog posts, and we're able to run it through an extremely inefficient system, but actually get something useful out of it with AI.
And this is why I think, or at least certainly one of the main reasons you wrote about the 2020s being the decade of data. What are some of the other things that make you feel like we're really at a potential inflection point for this magical material?
Well, I mean, just look at the capex spending of Meta and Google, 250 to 300 billion in data center spend. And you read the public earnings of all of those companies, they're capacity constrained. There's way more demand for AI consumption than they can supply. Meta is building one that's larger than Manhattan. One of them that's slated to be produced will consume more electricity than the country of Ireland.
Wow.
When you get a sense of the scale of the computers, the data centers, but the really computers that we're building, I was reading a research report, we think in 5 years 15% of American electricity, which is growing, the demand, 15% will be used to feed data centers. That gives me goosebumps. I'm so excited because it just tells you how valuable all of these data pipelines are and the demand for those kinds of insights.
Given, you know, what you said about your intern Alex who was talking about, you know, the things down to the chip level, do you look at companies like in the hardware stack and, you know, down to the chip level? Like is that something that you would theoretically invest in or no, too far afield?
By exception. There's a very particular set of expertise that you need at the chip level. I mean, there's a whole field of EDA, which is like CAD drawings for these chips. There's the assembly of chips on one side and power management on the other. It's a fascinating domain. I think the hard part there, a couple of challenges at least for a fund of our relatively small scale. The first is the amount of capital required for a lot of these chip companies is pretty significant. The second is if they make a mistake on tape out, which is kind of the final rendition, it's extremely expensive. And then the third is the number of potential buyers is ultimately pretty limited. I mean, you look at the EDA market, the software market, there are two or three publicly traded companies like Synopsys is one, Cadence is another that could buy these kinds of companies. There will be breakouts, there is no doubt, but I think it's hard for us. And then the other dynamic there is you have all of the major hyperscalers investing in their own silicon. So you have Google with the TPUs and that's not going away and Amazon with the inference unit chips and I forget the name of the training chips and Microsoft has theirs and Meta has created open-source architectures that they've released. So I think it's a big boy's game.
Yeah, hard to break in as an insurgent. On the crypto side, you know, you've been interested in crypto for a long time and you really are interested in it for the sort of core technology rather than, you know, a lot of the mania that surrounds it. You know, a decade, decade and a half in depending on how you want to judge it, how do you think about the progress crypto has made as an industry? Like where do you sort of see it in the cycle of development?
I think it's broadly underappreciated and it's been extraordinarily massive. I mean, you look at Bitcoin, for a new generation it's gold. It's the equivalent of gold. People trust it more and I think that's a pretty phenomenal statement to say we've had an asset that has existed for thousands of years in gold that people trust as an ultimate store of value and now we have a digital equivalent. And I think it's, you know, less than 50 basis points of global wealth is in Bitcoin and most of the projections say it's going to two or three. So, that's pretty significant. I think the second thing that's really happened within the world of crypto that we're seeing now is the broad acceptance within the US of stablecoins.
Absolutely trans- I mean, by the end of the year, I bet most major large banks in the US have their own stablecoin project, a pretty significant fraction. Like 5 to 10% of US dollars moving through systems will likely be through stables. And I think 2 years ago that would have been unfathomable.
Yeah, that seems like it's happened insanely fast. Like I remember writing about it just- yeah, probably about two or three years ago at this point and it still felt like there was a certain group of people in crypto for whom it was so obvious that it was almost a boring thing to write and then for a large swath of the world like still very, very strange and hard to wrap your head around.
Right. Jamie Dimon said very famously crypto is rat poison and now JP Morgan has an internal blockchain where they move 1 to 10 billion dollars a day on it for international settlement. So, we've come a long way. You know, and then I think the third trend that we're paying a lot of attention to is the tokenization of stock. So, Robinhood is doing this and Coinbase is doing this and I think there's two really interesting axes here. So, typically when you buy a stock, you buy it on the New York Stock Exchange or the Nasdaq. That's called a venue. And if you wanted to buy a token, let's say you wanted to buy Solana or Ethereum, you would buy it on another venue. You might buy it on Coinbase, which is a centralized exchange. You might buy it on a decentralized exchange like Uniswap. But you can't buy stocks using crypto exchanges and you can't buy tokens using stock exchanges. But the brokerage is bridging them. So, Robinhood today, you can buy crypto and you can buy stocks. Where the venue is, where the asset underlying doesn't matter. And then now what you can do is you can buy synthetics. Robinhood is offering shares of OpenAI that you can buy. And it's on a blockchain. It's a tokenized stock. Now, there's a lot to unpack there. But what does this mean? Well, it means that what's really exciting for crypto is you have the entire US stock market, which is the largest stock market in the world, and then you have crypto, which is large but not as large. And all of a sudden those pools of capital should fuse, which is great. The other thing it means is that the startups should have a much faster path. I think software startups will have a much faster path to IPO as a result of crypto than they've had in the last 10 years.
Oh, wow, interesting. I want to unpack both of those quickly, but the first part, like you say they should fuse. Can you explain to folks why that almost is an inevitability that, you know, these things are going to come together from an architectural advantages standpoint?
Yeah, I mean, there's no real difference between a token and a stock, right? What do you have with a stock? You have a voting right, depending. You have a share in the company. You have a dividend right. Let's just say it's those three and the ability to trade it, right? So, you have those three things. Well, a token is the same thing. I have a dividend right. It can produce yield for me. I can vote and I can trade it. And so, okay, securities law, I think will ultimately catch up and say both of these things are the same thing. So, legally it's- and there are already significant volumes of debt, like bonds, that are at crypto exchanges that are traded just as they would be on bond markets. So, that market was- the bond market was the first one to normalize relations, let's say. And the equities market is coming. The other thing that's happening is publicly traded software companies trade on multiples, right? We talk about forward multiples, EV to NTM. And for a long time crypto tokens did not. I mean, you look at some of these multiples, they were in the tens of thousands of times of revenue.
And over the last 6 months, certain categories of crypto tokens are now trading at 40 to 60 times revs. So, still elevated, but we're now achieving normalization. And so, if I'm a software investor and I have a dollar to invest, and it's just as easy for me to invest in the equity market as a token market, and I have a reasonably good proxy of financial statements between the two, now all of a sudden my dollars can flow freely, and I'm satisfying my fiduciary responsibility to do diligence on both of them, which is lacking today in the token world. There's no GAAP, there's no S-1. Right, but it's coming.
How does this change end up accelerating the timeline to IPOs for some of these software companies, do you think?
How much does it cost to go public? I'm not talking about the dilution or the, you know, the amount of money raised. I'm not talking about the legal fees, investor relations, the regulatory fees.
What do you think it costs to take a software company public?
Gosh, I honestly have no idea. I would put it in those sort of like single-digit millions.
Okay, well, I'm off by a good chunk there.
Okay, so if you're a $100 million revenue company, is it rational to raise a round of financing that costs you 15 to 25 million?
So, to put it in perspective, if you were going to raise a Series X, very late-stage round,
your legal fees might be in the hundreds of thousands of dollars. You might touch a million depending on how big your cap table is. You know, Series A is 30K, Series B is 40K, Series C is 50K. So, all of a sudden you have a step up of like three or four orders of magnitude in just your transaction costs to go public, which is why it used to be in the late '90s you needed like 25 million of trailing revenue to go public. And today, no, no, no, you can't go public unless you have 250, maybe 500 million in revenue because as an expense it'd be bananas or just raise it in the private markets. And so that's why you look at the average growth of publicly traded companies, it's asymptoting to this 10% basically, which is software inflation, because it's so expensive to go public. So, why is it so expensive? Well, there's just a lot of regulation, right? Sarbanes-Oxley, all that kind of stuff. And so if you look at crypto exchanges, the regulation there is much less. There's no S-1, there's no audit, and so some of those components are important, but the point is we have made it so expensive to go public that if you're a microcap software company, if you're worth somewhere between one and a half to two billion, it's not economic to go public. Most of those companies get taken out by PE right away. Wouldn't it be amazing if you had a venue where small cap high growth software companies were publicly traded. And so that's what gets me so excited. And these exist. You look at ChiNext in China or the ASX in the UK or TSX or the rumors of the Texas Stock Exchange, which would be a new venue for trading. All of those venues are focused on high growth small cap technology companies where the disclosure requirements are significantly less than the New York Stock Exchange or the Nasdaq.
Wow, how interesting. You also mentioned, you know, the Robinhood OpenAI example, which is more like, you know, secondaries trading, which feels like an exciting other asset class that sort of needs to be opened up. But there's all these sort of complexities about like are these essentially options? Is it, you know, owned through an SPV? And who owns it? How do you see that ending up playing out?
Well, I've been reading online trying to understand because Robinhood mentioned the OpenAI tokenized stock and OpenAI said we did not authorize this. So, in most secondary transactions, the board must authorize those transactions. And so, my understanding, which is only based on what I've read online, is that Robinhood is creating a synthetic asset that tracks the value of OpenAI stock, and they're backstopping it. And maybe there's an SPV underneath. Anyway, it's not clear.
Unclear, yeah. We'll see how it all shakes out, I suppose.
But I do think the notion of tokenized secondaries, or secondaries that float, or even tokenized venture firms, where LPs can trade underlying positions, is important. Let me reframe venture capital the way that PE works today. I start a seed fund. I find a company, two people, and a dog, and I help them get to a Series B. And I work with them for 4 years, and then I sell the entirety of my position. And then a Series B specialist fund that is focused on scaling go-to-market buys that entire position, and grows the company from a million in ARR to 25 million in ARR, and gets the benefit of both the revenue growth and the multiple expansion associated with the revenue growth, and then sells it to a Series E investor. And I'm just making things up. And that Series E investor is really good at preparing companies to go public. They have the right Rolodex of executives, they know the investment bankers, and they go from Series E to IPO. That's the way that a large part of the private equity market works, and there are a couple of benefits. The first is the time for investors to get their money back, the DPI, dollars to paid in, is much faster, which makes subsequent fundraising much faster. There's specialization on individual stages. And so the cycle of money basically just moves a whole lot faster. We're nowhere close to that, right? We talked about venture capital as a $250 billion asset class. In the last 3 years, the totality of all secondary funds is 6 billion. So, it's, you know, it's nowhere- talking maybe a basis point. We're not there yet. But I wonder- one of the questions in my mind is I wonder if we get to a place where seed funds are liquidating positions after three or four years. So, these A funds are liquidating. Maybe not the entirety, but some fraction thereof.
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You know, we were talking about some of these crypto innovations and, you know, I'm reminded of a piece I think you wrote in early 2024 where you talked about the most profitable software startup in the world is Ethereum.
And I thought that was such a good framing and such an interesting way that you talked about it. It feels like it's been a really sort of tough cycle for Ethereum in general. There's lots of soul searching, lots of discussion about where things head. How have you sort of looked at that? How do you see its place in the ecosystem? You know, I do think there's such a clear story around Bitcoin as you said and a clearer one around Solana. But, you know, are people too down on Ethereum? Like how do you think about its potential today?
Yeah, I love, you had a brilliant find in there. You said is Ethereum soul searching? So, just for the audience, Solana's nickname is Soul.
There you go. That's right.
Right. And so, the major competitor to Ethereum is Solana. So, I think Ethereum is kind of the grandparent of all of these chains and the volumes, I mean just to kind of put it in perspective, 50 to 60% of all stablecoin volume is on Ethereum and another big chunk is on Tron. So, it's really the vast majority part of the market and then 60% plus of the decentralized finance or DeFi market is on Ethereum. So, it's the big dog.
And Ethereum, it plateaued, right? There was not a lot of innovation. They allowed other companies to innovate on top, which are called layer twos like Arbitrum and Optimism. And they were solving, those L2s were solving performance challenges for the ecosystem. And so, they were basically allowing you to move money faster and cheaper than Ethereum and saving you 90% to kind of give you a sense of the relative efficiencies of those systems. And then Solana came around and said, "We're going to architect in a very different way. We'll be more centralized. It will be faster and cheaper." And then you have another one called Sui, which I was lucky enough to be an investor in, that also has very, very significant performance improvements. That's the ex-Meta blockchain team, one of the two. And so, within the span of 3 years, you had two orders of magnitude improvement in blockchain performance relative to Ethereum. Let me ground that in an example. If I wanted to send you a CryptoKitty, it would cost me $50 to send it to you on Ethereum. If I used an L2 like Arbitrum, it might cost me $2.50. And then if I use a more modern blockchain like Solana or Sui, it might cost me $0.20. Right. So, very significant reduction in transaction costs.
And so, as a result, over time, well, developers will build on the systems that are more efficient, much better price performance characteristics. Nobody wants to pay those fees. And so, that's where we found ourselves with ETH maybe 3 to 4 months ago. And then people started, all of a sudden...
Yeah, dissatisfaction. The community decided, okay, we need to react. So, they raised the $150 million, and Vitalik is more involved, and they're at this crux, this critical moment in the blockchain's development where they need to figure out what their competitive advantage is. It's a little bit like AWS before AI. It was the standard. Everybody, I mean, it was not even a question if you were a startup which platform you were building on, AWS. And then AI came around. No, Azure became the dominant platform. Why? Because they had a special relationship with OpenAI. And so, Solana has a special relationship with Stripe. Right? Robinhood has a special relationship with Hyperliquid. And now all of a sudden you have bigger strategic relationships that change the builders' perspectives on which platform to build on. And so, Ethereum finds itself where AWS is or was 6 or 7 months ago. Which is there's been this huge wave of innovation, other people have pushed, and now the developer mindset is shifting.
As you think about its competitive advantages and what should be the real advantages of the project, like what do you think that should look like? Like, what do you see as the things that the grandfather still has or should lean into that these younger chains maybe can't compete with or will struggle to compete with?
I think the most important thing in any financial market is liquidity. And Ethereum has it now, right? So, the question is, how do you capture that liquidity? Well, stablecoins will be an absolutely essential market. And minimizing the transaction costs so that liquidity remains on ETH is priority one. How do they do that? What do they do with the L2s? How do they think about the consensus infrastructure? And then the reward systems for the validators. I think it's a really... Basically, how do you architect your entire system?
They'll have to, I think, revisit a lot of the core assumptions because the underlying technology has changed. And that's okay, but I think a lot of times in the world of Web3, we have attachments to certain ideas and over time they change.
Really interesting. As you sort of look at the crypto Web3 landscape, like, are there newer projects that you've, you know, spent a lot of time playing with that you think are really promising or new sort of pieces of infrastructure that you think are, you know, worth discussing that aren't being as discussed right now?
Well, I mean, there's a brand new company called Hyperliquid that's worth somewhere between 20 to 40 billion that outside the world of crypto is not very well known, not venture-backed. And they did a couple of things that were absolutely brilliant. One, they focused on the perpetuals market, highest margin product. They created a blockchain that has some unique attributes to that market in particular. So, they specialized a vertically integrated stack exclusively on it. And so, as a result of the vertical integration and then making the blockchain specific and the tokenomics and all that stuff specific to what they were doing, they built a huge, I mean, multi-decacorn business that's now partnering with Phantom, right? So, Phantom now you can trade perps and it's all powered through Hyperliquid.
And I think, as you said, like no venture capital and turned down a lot of venture capital as far as I know, which is, yeah, pretty cool.
Really cool. You know, $30 bootstrap.
Yeah, yeah, pretty amazing.
Really. And then, you know, they're doing all kinds of other things where they buy their tokens back, right? It's like a stock buyback program just like Apple. And so, they're actively managing the value of their token. A lot of foresight and they deserve a lot of credit for the company that they've built. So, I think the vertical integration is one really interesting trend. I think, you know, another big question is are we moving from proof of work to proof of stake to proof of authority?
Can you explain those for folks just very briefly? I know that's not the easiest, but in simple terms.
Yeah, so Bitcoin is proof of work. If you want to earn money by minting Bitcoin, you need a really big computer and you basically solve very complex, not complex, but computationally intensive math problems and then you're rewarded with a fraction of a Bitcoin. That's proof of work. Proof of stake is someone is vouching for me. So, if I'm trying to join a, I don't know, whatever, social club, right? And Mario vouches for me, that's proof of stake. He's staking his reputation. People do that in the financial world like, I know Mario's trading, I've got him.
